@inbook{5918da778c684291964e3f28557b338e,
title = "“Take it or Leave it”: Effective Visualization of Privacy Policies",
abstract = "As per country law, service providers are obliged to share their business practices with users in the form of a privacy policy. However, considering the complexity of privacy policies, it is questionable to what extent they actually achieve their goal of informing the users. Policies are typically unclear, difficult to understand and time-consuming to read. In this paper, analyzing more than 600 privacy policies of popular websites in India, we present a solution, which can assist users when they are navigating online. The tool performs a semi-automatic analysis and visualization of the privacy policy of the website they visit, and also facilitates access to the reputation of the site. Our solution uses a Na{\"i}ve Bayes algorithm to classify the privacy policy text across 8 subsections, identified in our previous study. Furthermore, it provides a summarized version of the policy to give users a quick overview of how the service provider handles their personal information. The results show that visual aids can indeed increase the readability of the privacy policy. At the end, we propose a recommended structure of the privacy policy, which can further enhance the user{\textquoteright}s privacy awareness and understanding of privacy policies.",
keywords = "Privacy, , privacy policy, , terms of use, , consent, , personal information, , natural language processing, , Machine Learning",
author = "Dhotre, {Prashant Shantaram} and Anurag Bihani and Samant Khajuria and Henning Olesen",
year = "2017",
month = mar,
day = "31",
language = "English",
isbn = "9788793519664 ",
series = "Wireless World Research Forum Series in Mobile Telecomunications",
publisher = "River Publishers",
pages = "39--64",
editor = "Samant Khajuria and S{\o}rensen, {Lene } and Skouby, {Knud Erik}",
booktitle = "Cybersecurity and Privacy",
}